Data Science Build, Train & Test A Machine Learning Model

What you'll learn
Using AI and Machine Learning to Predict Chance of Admit into Universities
Building, Training, Testing and Evaluating Machine learning Models
Learn to create heatmaps, correlation tables, scatter plots and distplot using Seaborn library
A-Z step by step guide into importing libraries, importing and exploring datasets, building a Machine learning model, training, testing and evaluating it.
Learn to work with Linear Regression Machine Learning Algorithm to create Machine Learning Models with approx 96 percent accuracy.
Importing, Exploring and Analyzing datasets and finding correlation between its variables
Requirements
Very basic knowledge of python and its libraries
Description
Have you ever desired to build, train and test a Machine Learning Model in a real-world application?Would you like to learn how to predict Chance of Admission into Graduate School using Machine Learning?If the answer to any of the question is "YES", then you will love this project.This is a Practical Hands-on Machine Learning Guided Project with a real-world application of Machine learning. You learn by Practice. No unnecessary lectures. No unnecessary details. Clear, Concise, to the point Course.By the end of this course, you will be confident in building. training and testing any Linear Regression Machine Learning Model and Implementing them in real-world scenarios. No prior Experience in Machine learning required. We will guide you from first to last: Every Single Step.Reviews: "Gosh, this was fast! I was so absorbed with the learning I did not even realise I went through it no-stop! Really, interesting, the material is...

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